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Objectives <p>To evaluate the diagnostic accuracy of artificial intelligence-assisted opportunistic chest CT for osteoporosis/osteopenia screening in a Chinese population.</p> Methods <p>This retrospective study included 1306 adults (≥ 55 years) undergoing concurrent chest CT and DXA during physical examinations (Apr 2015 to May 2024). Exclusion criteria comprised vertebral fractures, spinal surgery, or contrast-enhanced CT. DXA T-scores (lumbar spine) defined osteoporosis, osteopenia, and normal BMD. The AI system automatically quantified volumetric BMD (AI-BMD) at vertebrae T10–L1. Diagnostic performance was assessed using ROC curves.</p> Results <p>Mean age was 63.96 years (36.98% male). Osteoporosis prevalence was 36.45% (<i>n</i> = 476/1306), significantly higher in women (<i>P</i> &lt; 0.01). AI-BMD values decreased significantly from T10 to L1 (<i>P</i> &lt; 0.05). For osteoporosis detection, AI-BMD demonstrated excellent diagnostic accuracy: AUC was 0.84 (95% CI: 0.81–0.87) at T10, 0.83 (95% CI: 0.80–0.86) at T11, 0.81 (95% CI: 0.79–0.84) at T12, and 0.83 (95% CI: 0.80–0.87) at L1. Performance for osteopenia diagnosis was moderate, with AUCs ranging from 0.72 to 0.75.</p> Conclusion <p>The combination of opportunistic chest CT and AI shows promise for accurate osteoporosis screening (AUCs 0.81–0.84), albeit with moderate performance in detecting osteopenia (AUCs 0.72–0.75). The retrospective, single-center design of this study suggests that future multi-center validation is warranted to confirm the generalizability of these findings.</p>

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Combination of artificial intelligence and chest computed tomography to assess bone mineral density

  • 期刊论文

  • 发表日期：

    2025年11月1日

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  • Lihao Wei,
  • Yanhua Qiu,
  • Weihua Lin,
  • Jiaming Lin,
  • Fang Yuan,
  • Yangyue Chen,
  • Jiguang Zhou,
  • Shanying Chen,
  • Ruigang Huang

摘要

Objectives

To evaluate the diagnostic accuracy of artificial intelligence-assisted opportunistic chest CT for osteoporosis/osteopenia screening in a Chinese population.

Methods

This retrospective study included 1306 adults (≥ 55 years) undergoing concurrent chest CT and DXA during physical examinations (Apr 2015 to May 2024). Exclusion criteria comprised vertebral fractures, spinal surgery, or contrast-enhanced CT. DXA T-scores (lumbar spine) defined osteoporosis, osteopenia, and normal BMD. The AI system automatically quantified volumetric BMD (AI-BMD) at vertebrae T10–L1. Diagnostic performance was assessed using ROC curves.

Results

Mean age was 63.96 years (36.98% male). Osteoporosis prevalence was 36.45% (n = 476/1306), significantly higher in women (P < 0.01). AI-BMD values decreased significantly from T10 to L1 (P < 0.05). For osteoporosis detection, AI-BMD demonstrated excellent diagnostic accuracy: AUC was 0.84 (95% CI: 0.81–0.87) at T10, 0.83 (95% CI: 0.80–0.86) at T11, 0.81 (95% CI: 0.79–0.84) at T12, and 0.83 (95% CI: 0.80–0.87) at L1. Performance for osteopenia diagnosis was moderate, with AUCs ranging from 0.72 to 0.75.

Conclusion

The combination of opportunistic chest CT and AI shows promise for accurate osteoporosis screening (AUCs 0.81–0.84), albeit with moderate performance in detecting osteopenia (AUCs 0.72–0.75). The retrospective, single-center design of this study suggests that future multi-center validation is warranted to confirm the generalizability of these findings.